It aims at gettting packages which specializes in alignment of
sequences produced by next generation sequencing.

The list to the right includes various software projects which are of some interest to the Debian Med Project. Currently, only a few of them are available as Debian packages. It is our goal, however, to include all software in Debian Med which can sensibly add to a high quality Debian Pure Blend.

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Med
to you, or if you have prepared an unofficial Debian package, please do not hesitate to
send a description of that project to the Debian Med mailing list

The BEDTools utilities allow one to address common genomics tasks such as
finding feature overlaps and computing coverage. The utilities are largely
based on four widely-used file formats: BED, GFF/GTF, VCF, and SAM/BAM. Using
BEDTools, one can develop sophisticated pipelines that answer complicated
research questions by streaming several BEDTools together.

This package addresses the problem to interpret the results from the
latest (2010) DNA sequencing technologies. Those will yield fairly
short stretches and those cannot be interpreted directly. It is the
challenge for tools like Bowtie to give a chromosomal location to the
short stretches of DNA sequenced per run.

Bowtie aligns short DNA sequences (reads) to the human genome at a rate
of over 25 million 35-bp reads per hour. Bowtie indexes the genome with
a Burrows-Wheeler index to keep its memory footprint small: typically
about 2.2 GB for the human genome (2.9 GB for paired-end).

BWA is a software package for mapping low-divergent sequences against
a large reference genome, such as the human genome. It consists of
three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. The first
algorithm is designed for Illumina sequence reads up to 100bp, while
the rest two for longer sequences ranged from 70bp to 1Mbp. BWA-MEM
and BWA-SW share similar features such as long-read support and split
alignment, but BWA-MEM, which is the latest, is generally recommended
for high-quality queries as it is faster and more accurate. BWA-MEM
also has better performance than BWA-backtrack for 70-100bp Illumina
reads.

The FASTX-Toolkit is a collection of command line tools for preprocessing
short nucleotide reads in FASTA and FASTQ formats, usually produced by
Next-Generation sequencing machines. The main processing of such FASTA/FASTQ
files is mapping (aligning) the sequences to reference genomes or other
databases using specialized programs like BWA, Bowtie and many others.
However, it is sometimes more productive to preprocess the FASTA/FASTQ files
before mapping the sequences to the genome—manipulating the sequences to
produce better mapping results. The FASTX-Toolkit tools perform some of these
preprocessing tasks.

KisSplice is a piece of software that enables the analysis of RNA-seq data
with or without a reference genome. It is an exact local transcriptome
assembler that allows one to identify SNPs, indels and alternative splicing
events. It can deal with an arbitrary number of biological conditions, and
will quantify each variant in each condition.
It has been tested on Illumina datasets of up to 1G reads.
Its memory consumption is around 5Gb for 100M reads.

LAST is software for comparing and aligning sequences, typically DNA or
protein sequences. LAST is similar to BLAST, but it copes better with very
large amounts of sequence data. Here are two things LAST is good at:

Comparing large (e.g. mammalian) genomes.

Mapping lots of sequence tags onto a genome.

The main technical innovation is that LAST finds initial matches based on
their multiplicity, instead of using a fixed size (e.g. BLAST uses 10-mers).
This allows one to map tags to genomes without repeat-masking, without becoming
overwhelmed by repetitive hits. To find these variable-sized matches, it uses
a suffix array (inspired by Vmatch). To achieve high sensitivity, it uses a
discontiguous suffix array, analogous to spaced seeds.

Maq (short for Mapping and Assembly with Quality) builds mapping assemblies
from short reads generated by the next-generation sequencing machines. It was
particularly designed for Illumina-Solexa 1G Genetic Analyzer, and has a
preliminary functionality to handle ABI SOLiD data. Maq is previously known as
mapass2.

Developmemt of Maq stopped in 2008. Its successors are BWA and SAMtools.

The mira genome fragment assembler is a specialised assembler for
sequencing projects classified as 'hard' due to high number of similar
repeats. For expressed sequence tags (ESTs) transcripts, miraEST is
specialised on reconstructing pristine mRNA transcripts while
detecting and classifying single nucleotide polymorphisms (SNP)
occuring in different variations thereof.

The assembler is routinely used for such various tasks as mutation
detection in different cell types, similarity analysis of transcripts
between organisms, and pristine assembly of sequences from various
sources for oligo design in clinical microarray experiments.

caf2fasta, caf2gbf, caf2text, caf2html, gbf2caf and gbf2fasta are some
frequently used file converters (realised through links to convert_project)

scftool: set of tools useful when working with SCF trace files

fastatool: set of tools useful when working with FASTA trace files

Scripts provided:

fasta2frag: fragmenting sequences into smaller, overlapping
subsequences. Useful for simulating shotgun sequences. Can create
subsequences in both directions (/default) and also paired-end sequences.

fastaselect: given a FASTA file (and possibly a FASTA quality file) and
a file with names of reads, select the sequences from the input FASTA (and
quality file) and writes them to an output FASTA

fastqselect: like fastaselect, only for FASTQ

fixACE4consed: Consed has a bug which incapacitates it from reading
consensus tags in ACE files written by the MIRA assembler (and possibly
other programs). This script massages an ACE file so that consed can read
the consensus tags.

Mothur seeks to develop a single piece of open-source, expandable
software to fill the bioinformatics needs of the microbial ecology
community. It has incorporated the functionality of dotur, sons,
treeclimber, s-libshuff, unifrac, and much more. In addition to improving
the flexibility of these algorithms, a number of other features including
calculators and visualization tools were added.

QIIME (canonically pronounced ‘Chime’) is a pipeline for performing
microbial community analysis that integrates many third party tools which
have become standard in the field. A standard QIIME analysis begins with
sequence data from one or more sequencing platforms, including

Sanger,

Roche/454, and

Illumina GAIIx.
With all the underlying tools installed,
of which not all are yet available in Debian (or any other Linux
distribution), QIIME can perform

library de-multiplexing and quality filtering;

denoising with PyroNoise;

OTU and representative set picking with uclust, cdhit, mothur, BLAST,
or other tools;

taxonomy assignment with BLAST or the RDP classifier;

sequence alignment with PyNAST, muscle, infernal, or other tools;

phylogeny reconstruction with FastTree, raxml, clearcut, or other tools;

alpha diversity and rarefaction, including visualization of results,
using over 20 metrics including Phylogenetic Diversity, chao1, and
observed species;

beta diversity and rarefaction, including visualization of results,
using over 25 metrics including weighted and unweighted UniFrac,
Euclidean distance, and Bray-Curtis;

summarization and visualization of taxonomic composition of samples
using pie charts and histograms
and many other features.

QIIME includes parallelization capabilities for many of the
computationally intensive steps. By default, these are configured to
utilize a mutli-core environment, and are easily configured to run in
a cluster environment. QIIME is built in Python using the open-source
PyCogent toolkit. It makes extensive use of unit tests, and is highly
modular to facilitate custom analyses.

Bioconductor package for differential expression analysis of whole
transcriptome sequencing (RNA-seq) and digital gene expression
profiles with biological replication. It uses empirical Bayes
estimation and exact tests based on the negative binomial
distribution. It is also useful for differential signal analysis with
other types of genome-scale count data.

This tool allows one to display very long data vectors in a space-efficient
manner, by organising it along a 2D Hilbert curve. The user can then
visually judge the large scale structure and distribution of features
simultaenously with the rough shape and intensity of individual features.

In bioinformatics, a typical use case is ChIP-Chip and ChIP-Seq,
or basically all the kinds of genomic data, that are conventionally
displayed as quantitative track ("wiggle data") in genome browsers such
as those provided by Ensembl or UCSC.

Samtools is a set of utilities that manipulate nucleotide sequence alignments
in the binary BAM format. It imports from and exports to the ascii SAM
(Sequence Alignment/Map) format, does sorting, merging and indexing, and allows
to retrieve reads in any regions swiftly. It is designed to work on a stream,
and is able to open a BAM (not SAM) file on a remote FTP or HTTP server.

Tools for reading the SRA archive, generally by converting individual runs
into some commonly used format such as fastq.

The textual dumpers "sra-dump" and "vdb-dump" are provided in this
release as an aid in visual inspection. It is likely that their
actual output formatting will be changed in the near future to a
stricter, more formalized representation[s]. PLEASE DO NOT RELY UPON
THE OUTPUT FORMAT SEEN IN THIS RELEASE.

The "help" information will be improved in near future releases, and
the tool options will become standardized across the set. More documentation
will also be provided documentation on the NCBI web site.

Tool options may change in the next release. Version 1 tool options
will remain supported wherever possible in order to preserve
operation of any existing scripts.

The Short Sequence Assembly by K-mer search and 3′ read Extension
(SSAKE) is a genomics application for aggressively assembling
millions of short nucleotide sequences by progressively searching for
perfect 3′-most k-mers using a DNA prefix tree. SSAKE is designed to
help leverage the information from short sequences reads by
stringently clustering them into contigs that can be used to
characterize novel sequencing targets.

Tabix indexes files where some columns indicate sequence coordinates: name
(usually a chromosme), start and stop. The input data file must be position
sorted and compressed by bgzip (provided in this package), which has a gzip
like interface. After indexing, tabix is able to quickly retrieve data lines by
chromosomal coordinates. Fast data retrieval also works over network if an URI
is given as a file name.

TopHat aligns RNA-Seq reads to mammalian-sized genomes using the ultra
high-throughput short read aligner Bowtie, and then analyzes the
mapping results to identify splice junctions between exons.
TopHat is a collaborative effort between the University of Maryland
Center for Bioinformatics and Computational Biology and the
University of California, Berkeley Departments of Mathematics and
Molecular and Cell Biology.

ECHO is an error correction algorithm designed for short-reads
from next-generation sequencing platforms such as Illumina's
Genome Analyzer II. The algorithm uses a Bayesian framework to
improve the quality of the reads in a given data set by employing
maximum a posteriori estimation.

VCFtools is a program package designed for working with VCF files, such as
those generated by the 1000 Genomes Project. The aim of VCFtools is to
provide methods for working with VCF files: validating, merging, comparing
and calculate some basic population genetic statistics.

Velvet is a de novo genomic assembler specially designed for short read
sequencing technologies, such as Solexa or 454, developed by Daniel Zerbino and
Ewan Birney at the European Bioinformatics Institute (EMBL-EBI), near
Cambridge, in the United Kingdom.

Velvet currently takes in short read sequences, removes errors then produces
high quality unique contigs. It then uses paired read information, if
available, to retrieve the repeated areas between contigs.

Cufflinks assembles transcripts, estimates their abundances, and tests for
differential expression and regulation in RNA-Seq samples. It accepts aligned
RNA-Seq reads and assembles the alignments into a parsimonious set of
transcripts. Cufflinks then estimates the relative abundances of these
transcripts based on how many reads support each one.

MosaikBuild converts various sequence formats into Mosaik’s native read
format. MosaikAligner pairwise aligns each read to a specified series of
reference sequences. MosaikSort resolves paired-end reads and sorts the
alignments by the reference sequence coordinates. Finally, MosaikText
converts alignments to different text-based formats.

At this time, the workflow consists of supplying sequences in FASTA,
FASTQ, Illumina Bustard & Gerald, or SRF file formats and producing
results in the BLAT axt, the BAM/SAM, the UCSC Genome Browser bed, or
the Illumina ELAND formats.

No known packages available

ANNOVAR is an efficient software tool to utilize update-to-date information
to functionally annotate genetic variants detected from diverse genomes
(including human genome hg18, hg19, as well as mouse, worm, fly, yeast and
many others). Given a list of variants with chromosome, start position, end
position, reference nucleotide and observed nucleotides, ANNOVAR can perform:

1. Gene-based annotation: identify whether SNPs or CNVs cause protein coding
changes and the amino acids that are affected. Users can flexibly use RefSeq
genes, UCSC genes, ENSEMBL genes, GENCODE genes, or many other gene definition
systems.
2. Region-based annotations: identify variants in specific genomic regions,
for example, conserved regions among 44 species, predicted transcription
factor binding sites, segmental duplication regions, GWAS hits, database
of genomic variants, DNAse I hypersensitivity sites, ENCODE
H3K4Me1/H3K4Me3/H3K27Ac/CTCF sites, ChIP-Seq peaks, RNA-Seq peaks, or many
other annotations on genomic intervals.
3. Filter-based annotation: identify variants that are reported in dbSNP,
or identify the subset of common SNPs (MAF>1%) in the 1000 Genome Project,
or identify subset of non-synonymous SNPs with SIFT score>0.05, or many
other annotations on specific mutations.
4. Other functionalities: Retrieve the nucleotide sequence in any
user-specific genomic positions in batch, identify a candidate gene list
for Mendelian diseases from exome data, identify a list of SNPs from
1000 Genomes that are in strong LD with a GWAS hit, and many other
creative utilities.

In a modern desktop computer (3GHz Intel Xeon CPU, 8Gb memory), for
4.7 million variants, ANNOVAR requires ~4 minutes to perform
gene-based functional annotation, or ~15 minutes to perform stepwise
"variants reduction" procedure, making it practical to handle hundreds
of human genomes in a day.

Forge is a classic "Overlap layout consensus" genome assembler written
by Darren Platt and Dirk Evers. Implemented in C++ and using the
parallel MPI library, it runs on one or more machines in a network and
can scale to very large numbers of reads provided there is enough
collective memory on the machines used. It generates a full consensus
alignment of all reads, can handle mixtures of sanger, 454 and illumina
reads. There is some support for solid color space and it includes built
in tools for vector trimming and contamination screening.

Forge and was originally developed at Exelixis and they have kindly
agreed to place the software which underwent much subsequent development
outside Exelixis, into the public domain. Forge works with most of the
common MPI implementations.

Remark of Debian Med team: Competitor to MIRA2 and wgs-assembler

This package was requested by William Spooner whs@eaglegenomics.com as
a competitor to MIRA2 and wgs-assembler.

*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 175436